Electrochemical glucose test strips, such as those used in the OneTouch® Ultra® whole blood testing kit, which is available from LifeScan, Inc., are designed to measure the concentration of glucose in a physiological fluid sample from patients with diabetes. The measurement of glucose can be based on the selective oxidation of glucose by the enzyme glucose oxidase (GO). The reactions that can occur in a glucose test strip are summarized below in Equations 1 and 2.Glucose+GO(ox)→Gluconic Acid+GO(red)  Eq. 1GO(red)+2Fe(CN)63−→GO(ox)+2Fe(CN)64−  Eq. 2
As illustrated in Equation 1, glucose is oxidized to gluconic acid by the oxidized form of glucose oxidase (GO(ox)). It should be noted that GO(ox) may also be referred to as an “oxidized enzyme.” During the reaction in Equation 1, the oxidized enzyme GO(ox) is converted to its reduced state, which is denoted as GO(red) (i.e., “reduced enzyme”). Next, the reduced enzyme GO(red) is re-oxidized back to GO(ox) by reaction with Fe(CN)63− the oxidized (referred to as either oxid mediator or ferricyanide) as illustrated in Equation 2. During the re-generation of GO(red) back to its oxidized state GO(ox), Fe(CN)63− is reduced to Fe(CN)64− (referred to as either reduced mediator or ferrocyanide).
When the reactions set forth above are conducted with a test signal in the form of potential applied between two electrodes, a test signal in the form of a current can be created by the electrochemical re-oxidation of the reduced mediator at the electrode surface. Thus, since, in an ideal environment, the amount of ferrocyanide created during the chemical reaction described above is directly proportional to the amount of glucose in the sample positioned between the electrodes, the test output signal generated would be proportional to the glucose content of the sample. A mediator, such as ferricyanide, is a compound that accepts electrons from an enzyme such as glucose oxidase and then donates the electrons to an electrode. As the concentration of glucose in the sample increases, the amount of reduced mediator formed also increases; hence, there is a direct relationship between the test output signal, resulting from the re-oxidation of reduced mediator, and glucose concentration. In particular, the transfer of electrons across the electrical interface results in the flow of a test output signal (2 moles of electrons for every mole of glucose that is oxidized). The test output signal resulting from the introduction of glucose can, therefore, be referred to as a glucose output signal.
The electrochemical biosensor noted above can be produced in enormous quantities, on the order of hundreds of millions and even billions of such biosensor per year. Production of a great number of batches of the same product lead inevitably to increased variation in the resulting product. This is driven by variation, among other factors of: manufacturing setting (production line); materials used; and volume throughput (stressing manufacturing ability). Generally, the task of good manufacturing practice is to limit the encountered variability by controlling all process and material parameters (settings, critical-to-quality factors, etc.) in line with the knowledge gained through a thorough characterization of the product and its manufacturability. However, no matter how good the operation side of the manufacture process is, a perfectly reproducible production line is never achievable. A balance is usually struck between the effort it takes to manufacture the product, yield achieved, the volume of product produced and the regulatory performance targets the product needs to satisfy. The finer the amount of control is exercised in manufacturing, the more expensive the overall product usually is.
One technique that others have used to deal with the variations in manufacturing is to accept a lower yield. For example, if there are wide variations on a yield of 90% of manufactured biosensors, the manufacturers could simply discard a large percentage (50% or more) of the biosensors that are outside acceptable manufacturing variations. This, however, results in waste and added cost due to the large number of discarded biosensors.
Another technique is to use calibration parameters, known as calibration slope and calibration intercept to those skilled in this field. Briefly, calibration curves can be generated by plotting measured glucose concentration against actual glucose concentration (or measured current versus YSI current), and a formula y=m*mx+c least squares fitted to the graph to give a value for batch slope m and batch intercept c for the remaining strips from the lot or batch. The graph can be divided into discrete areas and a code assigned to each area within the graph. The code itself is indexed to both the intercept and slope for a particular batch on which the calibration was performed thereon.